Computer vision techniques, in conjunction with acquisition through remote cameras and
unmanned aerial vehicles (UAVs), offer promising non-contact solutions to civil infrastructure …

Appearance and motion are two important sources of information in video object
segmentation (VOS). Previous methods mainly focus on using simplex solutions, lowering …

In this paper, we focus on designing effective method for fast and accurate scene parsing. A
common practice to improve the performance is to attain high resolution feature maps with …

Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

Semantic segmentation requires large amounts of pixel-wise annotations to learn accurate
models. In this paper, we present a video prediction-based methodology to scale up training …

Video segmentation—partitioning video frames into multiple segments or objects—plays a
critical role in a broad range of practical applications, from enhancing visual effects in movie …

In this paper, we present a new large-scale dataset for the video panoptic segmentation
task, which aims to assign semantic classes and track identities to all pixels in a video. As …

Can our video understanding systems perceive objects when a heavy occlusion exists in a
scene? To answer this question, we collect a large-scale dataset called OVIS for occluded …

Semantic segmentation is a challenging task in computer vision systems. A lot of methods
have been developed to tackle this problem ranging from autonomous vehicles, human …

Deep learning approaches to optical flow estimation have seen rapid progress over the
recent years. One common trait of many networks is that they refine an initial flow estimate …